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A real BuzzView analysis in this category
bsurance’s AI visibility across ChatGPT, Google AI Overviews & Perplexity — one of the brands tracked in this category, straight from the live tool.
We sent 20 real buying questions to ChatGPT and Google AI Overviews – the questions businesses in this category actually ask. Then we counted which providers get named, and how often. The result is a ranking built from real AI answers, not opinion.
Qover (4.4%) and Check24 (4.4%) dominate the answers – the remaining 95 named providers split what's left. If you're not here, you simply don't exist to AI users. That's exactly the gap BuzzView makes visible.
Share of all brand mentions across 20 prompts (Share of Voice). The longer the bar, the more often AI names the provider – across every question tested.
Behind the ranking — what the numbers actually mean for brands in the insurtech space.
Across 20 real buying prompts, AI systems surfaced 95 distinct insurtech providers, generating a total of 183 brand mentions. That number alone tells a story. In mature software categories such as CRM or cloud storage, the same prompt volume typically returns a far tighter cluster of names. The breadth here — nearly five unique providers per mention slot, on average — signals that AI has not yet converged on a settled mental model of who "owns" the insurtech space.
The top six providers — Qover, Check24, Allianz, bolttech, AXA, and bsurance — together account for 40 mentions, which is 21.9% of the total. That is a remarkably thin concentration for a category where several players have operated for more than a decade. By contrast, in categories such as project management or marketing automation, the top six typically command 50 to 70% of all AI-generated mentions. Insurtech's long tail is unusually thick.
The remaining 83 providers share 115 mentions between them, averaging roughly 1.4 mentions each. This is characteristic of what researchers call a power-law distribution with a very shallow head — a pattern found in markets where product differentiation is high, use cases are fragmented, and no single brand has yet achieved the kind of ubiquitous reference status that Salesforce enjoys in CRM or Stripe in payments. For insurtech, the battleground is still wide open at the AI layer.
What drives this fragmentation? Insurtech is fundamentally a vertical industry where the right solution depends on the use case: embedded insurance for e-commerce platforms requires different tooling than digital claims automation for enterprise carriers, which differs again from consumer-facing comparison portals. AI systems reflect this reality by recommending different providers for different problem frames. Brands that clearly articulate their vertical specialization in publicly indexed content are better positioned to capture consistent mentions within their niche rather than competing for generic category share.
In a category this fragmented, owning a well-defined vertical niche in AI-readable content is more effective than competing for broad category mentions. The top 6 claim only 22% of the space — the remaining 78% is up for grabs.
Among the five tracked providers, visibility scores range from 62.5% (bsurance) down to 25.0% (Element), with Neodigital and hepster tied at 50% and omni:us sitting at 37.5%. This 37.5-percentage-point spread between the most and least visible tracked provider is substantial given that all five operate in the same broad insurtech category. It means bsurance appeared as a relevant answer in 12.5 out of 20 prompts, while Element was relevant in only 5. That is not a coincidence of brand age or market size alone.
The primary driver of visibility in insurtech appears to be the depth and breadth of publicly indexed technical and use-case documentation. bsurance has invested heavily in partner-facing content, API documentation, and case studies aimed at the embedded insurance integration vertical. This content exists in a form that AI systems can parse and cite when a buyer asks: "Which embedded insurance provider is best for my e-commerce platform?" The answer doesn't come from brand recognition alone — it comes from the quality of the training-relevant corpus a brand has built around its specific problem domain.
Element's lower visibility score (25%) likely reflects a narrower content footprint focused on B2B insurance-as-a-service infrastructure, a use case that generates fewer explicit prompt categories. omni:us, which specializes in AI-powered claims automation, sits at 37.5% visibility with a 10% share of voice — suggesting that when it is mentioned, it appears multiple times, but the absolute number of prompts where claims automation is the central question is limited in this dataset's 20-prompt scope.
The visibility gap between 62.5% and 25% matters because AI search is not a single channel — it is a distribution layer. A provider visible in 62.5% of prompts is effectively present at the decision moment of 12-13 out of every 20 prospective buyers who use AI to research the category. A provider at 25% visibility is present at only 5. If AI-assisted research continues to grow as a discovery channel in B2B insurance and fintech procurement, that gap translates directly into pipeline differential at the very top of the funnel.
The 37-point visibility gap between bsurance and Element correlates with content depth, not company size. In insurtech, AI visibility is earned through indexed use-case documentation and integration guides — not just brand awareness campaigns.
The 20 prompts in this study represent four distinct buying intents. Best-of prompts ("What are the best embedded insurance tools for SMBs in Germany?") surface category leaders with broad name recognition — this is where Allianz, AXA, Check24, and Verivox tend to appear, because AI associates them with established market authority. These prompts reward brands that dominate general-purpose review platforms, industry awards lists, and mainstream business media coverage. The winners here are not necessarily the most technically sophisticated providers; they are the most frequently cited across a wide range of sources.
Comparison prompts ("Compare bsurance, Neodigital, and AXA in the area of digital insurance") produce a different winner set. Here, providers with rich comparison-ready content — structured feature tables, third-party analyst coverage, or head-to-head review pages — perform better. bsurance and hepster surface consistently in this category because their positioning is tightly defined and their differentiators are explicitly articulated in indexed content. AI systems can construct a meaningful comparison only if the source material actually makes a comparison possible.
Alternative-seeking prompts ("What alternatives are there to Competitor A for embedded insurance?") are the highest-value prompt type for challengers. These prompts are explicitly shopping behavior — the buyer has already rejected one option and is actively looking for substitutes. Providers like Clark and Getsafe, which have positioned themselves as modern alternatives to legacy insurers, tend to surface here. This is where content that directly addresses competitive displacement ("Why companies switch from X to Y") earns disproportionate AI visibility.
Vertical and use-case prompts ("What are the best insurance tools for private customers in Germany?") surface the most niche-specific results. omni:us appears here in claims automation contexts; hepster and bsurance appear in the embedded insurance for SMBs context. The content strategy implication is that a single landing page optimized for a specific combination of use case and customer segment — rather than a generic product page — is the highest-leverage asset for AI visibility in this prompt type. Providers that invest in this vertical content architecture will systematically outperform those that rely on homepage-level messaging.
No single insurtech provider wins across all four prompt types. Sustainable AI visibility in this category requires a content architecture that addresses best-of, comparison, alternative-seeking, and vertical use-case queries separately — each with dedicated, deeply specific content.
Of the 12 providers in the leaderboard, only a subset generate positive sentiment from AI systems: Check24 leads with 4 positive mentions out of 8 total (50% positive rate), followed by Getsafe with 3 positive out of 5 (60%) and Clark with 3 positive out of 5 (60%). Verivox earns 2 positive mentions out of 5, and HUK-Coburg and CosmosDirekt each receive 2 positive mentions out of 4. These are the brands that AI systems actively recommend rather than merely cite — a meaningful distinction for buyers in a high-trust category like insurance.
At the other end of the sentiment spectrum, Qover is the only provider in the leaderboard to receive a negative mention — 1 out of 8 total citations. Bolttech, AXA, and bsurance receive exclusively neutral mentions, meaning AI surfaces them as relevant options but does not frame them with positive language. Neutral mentions are still valuable — they indicate presence and relevance — but they differ qualitatively from positive mentions, which typically include phrases like "highly recommended," "user-friendly," or "strong reviews" that actively nudge buyer behavior.
What drives positive sentiment in insurtech AI responses? The clearest pattern across Getsafe, Clark, and Check24 is heavy investment in consumer-facing review platforms, transparent pricing communication, and customer outcome stories. Getsafe and Clark both built their public profiles on independent review sites such as Trustpilot and Google Reviews, where high ratings create a durable signal in AI training data. Check24 benefits from its position as a price-comparison aggregator — a role that is inherently framed as consumer-beneficial in journalistic and user-generated content.
The predominantly neutral sentiment landscape for B2B-focused insurtechs like bolttech, AXA, omni:us, and bsurance reflects a structural gap: these providers have strong product reputations within their partner ecosystems, but that expertise lives in whitepapers, partner portals, and sales decks — formats that are either not indexed or not well-weighted by AI systems. Translating internal credibility into publicly visible, sentiment-positive content — case study landing pages, customer video testimonials, third-party analyst quotes — is the lever that converts neutral AI citations into positive ones.
Sentiment in AI responses is driven by publicly indexed review signals and outcome-focused content — not by product quality alone. Insurtechs with strong B2B reputations but thin consumer-facing review profiles should treat Trustpilot and case study pages as direct AI visibility infrastructure.
The full data picture — 95 distinct providers, 183 mentions, no single brand above 4.4% share of voice — places the insurtech category firmly in the "emerging" phase of AI visibility maturity. In mature AI search categories, a small cohort of two to four providers typically holds 40 to 60% of all mentions, and the ranking is stable across different prompt phrasings. In insurtech, the top two providers (Qover and Check24, each at 4.4%) together hold less than 9% of total mentions. This is closer to white noise than dominance, and it is an extraordinary window of opportunity for challengers.
The fragmentation also reflects the genuine structural complexity of the insurtech market, which spans at least five distinct sub-categories: embedded insurance (bsurance, bolttech, hepster), digital insurance comparison (Check24, Verivox), digital-native direct insurers (Getsafe, CosmosDirekt, Clark), AI claims automation (omni:us), and digital insurance infrastructure / B2B SaaS (Element, Neodigital). AI systems are correctly treating these as related but distinct problem domains, which is why no single provider emerges as an across-the-board winner. The category has not yet produced its Salesforce moment — a brand so dominant in AI memory that it is mentioned reflexively regardless of prompt specifics.
What does this mean in practical terms? It means that the AI visibility hierarchy in insurtech is not yet locked in. Categories that reach maturity — where two or three brands capture 40%+ of AI mentions — tend to remain stable because AI training data reinforces existing associations through repetition. Insurtech has not yet crossed that threshold. A provider that systematically builds AI-visible content assets over the next 12 to 18 months can realistically move from 3% to 10–15% share of voice, because the category's distributional center of gravity has not yet settled.
The actionable implication: brands that invest in AI visibility now — through structured content programs targeting each of the four prompt types, third-party citations, review platform density, and vertical use-case documentation — are investing at the lowest possible cost of entry. Once the category matures and two or three dominant brands absorb 50%+ of AI mentions, displacing them will require an order of magnitude more effort. The window when insurtech AI visibility can be shaped rather than merely competed for is open. Based on the current data, it will not stay open indefinitely.
With no provider above 4.4% share of voice across 95 competitors, insurtech's AI visibility hierarchy is still being written. Brands that act now — with structured, niche-specific content programs — can establish positions that will be difficult and expensive for later entrants to displace.
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No wishful thinking: the ranking comes from exactly these prompt types – best-of questions, comparisons, alternatives and use cases.
Visibility score = share of prompts where the provider appears in the AI answer at all. 100% means: present for every relevant question.
bsurance’s AI visibility across ChatGPT, Google AI Overviews & Perplexity — one of the brands tracked in this category, straight from the live tool.
We set the real search and buying questions of your industry – exactly how your customers actually ask AI.
Every prompt runs against all major AI models. We count mentions, position, sentiment and the cited sources.
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